Systems and methods for indicating a quality of grouped items

ABSTRACT

Systems and methods for determining a relative quantity of recyclable items with respect to a total number of items are disclosed. In one embodiment of the present invention, a computer-implemented method includes reading an identifier respectively associated with at least some of a total number of items. The computer determines a number of identifiers associated with the recyclable items. The computer also receives the total number of items, and computes the relative quantity of recyclable items by dividing the number of identifiers associated with the recyclable items by the total number of items.

RELATED APPLICATIONS

This application is related to the following copending and commonlyassigned patent applications, which are incorporated herein by referencein their entirety: “Systems and Methods for Measuring the Purity ofBales of Recyclable Materials,” having application Ser. No. ______ andattorney docket 105452-319, filed on Sep. 6, 2006; “Systems and Methodsfor Identifying and Collecting Banned Waste,” having application Ser.No. and attorney docket 105452-308, filed on Sep. 6, 2006; “Systems andMethods for Identifying Banned Waste in a Municipal Solid WasteEnvironment,” having application Ser. No. 11/433,505, filed on May 15,2006.

BACKGROUND OF THE INVENTION

1. Field of the Invention

Embodiments of the present invention relate to systems and methods forindicating a quality of grouped items and, more particularly, to aquality of grouped items generated, for example, within a materialrecovery facility (MRF).

2. Background Description

Waste management companies provide residential, commercial and municipalwaste management and recycling services for communities andorganizations. Customers can include single residences, companies, orentire towns. Municipalities often contract with or otherwise engage awaste management service provider to handle both its municipal solidwaste (MSW) and/or as its recycling services. MSW is garbage, refuse,and other discarded materials that result from residential, commercial,industrial, and/or community activities. MSW does not include bannedwaste, animal waste used as fertilizer, or sewage sludge.

Municipalities also encourage, or even require, recycling of selectedmaterials including, but not limited to, paper, cans, plastic bottles,and glass. Generally, these materials are picked up either by a wastemanagement company or a by municipality and taken to a material recoveryfacility (MRF), which is a facility that separates, processes, stores,and re-sells recoverable materials that have been collected.

At a MRF, materials are initially sorted by a variety of mechanical andmanual means. The materials are further sorted and grouped by categoryand, within the category, sorted by quality. For example, clear glass isseparated from colored glass, paper is separated from cardboard, andplastics are separated by type and color. Then glass is separated intovarious colors, where some colors are recycled more than other colors.When the final sorts are finished, some materials, such as plastic,steel, aluminum, paper, and cardboard are compressed into bales by largepresses, and sold to customers who convert the baled material intoconsumer products.

Problems associated with the above described material sorting processare that it is material specific, inefficient to implement, andexpensive. For example, the initial sort for identifying each item ofwaste is done by a person, which makes sorting inefficient andexpensive. Another example is sorting plastics by using an opticaldevice to determine various types of plastic. However, such opticaldevices are specific to the plastic, expensive to implement, useful onlyfor a range of plastic recyclables and are limited to line-of-sightidentification. Finally, eddy-current systems are useful only inconnection with metal recyclables. With line-of-sight identificationsystems there are problems such as false identifications, and a processthat is time and labor intensive. Thus, although these various processesand techniques are helpful for recycling, the end result is that errorsin sorting occur, and sorted material is often commingled withun-separable, non-recyclable material and items.

Another problem with the material sorting processes is thatmunicipalities continue to encourage and, in many cases, requirerecycling and reuse of recoverable materials, resulting in a growingamount of potentially recyclable material. This recyclable materialbecomes more commingled with non-recyclable materials as less care istaken to recycle properly by those required to recycle, leading to theaforementioned sorting issues of being material specific, inefficient toimplement, and expensive. In the end, the quality of the sortedmaterials that are produced as commodities for sale declines, sometimessignificantly. For example, many recoverable materials are convertedinto large bales before being sold, and these bales often becomecontaminated with non-recyclable material. The final recyclables to besold may become so contaminated that a customer becomes unsatisfied withthe quality (e.g., a low ratio of recyclables to non-recyclables and/orcontaminated materials). The recycler may therefore need to accept adowngraded price (lower quality product) or returned product.

In view of the foregoing, we have discovered that there is a need toprovide an accurate and verifiable measurement of the quality (e.g.,percent purity) of a commodity within, for example, a bale of recoveredmaterial(s).

SUMMARY OF EMBODIMENTS OF THE INVENTION

Systems and methods for determining a relative quantity of recyclableitems with respect to a total number of items are disclosed. In oneembodiment of the present invention, a computer-implemented methodincludes reading an identifier respectively associated with at leastsome of a total number of items. The computer determines a number ofidentifiers associated with the recyclable items. The computer alsoreceives a total number of items, and computes the relative quantity ofrecyclable items by dividing the number of identifiers associated withthe recyclable items by the total number of items.

In another embodiment of the present invention, a computer-implementedmethod for determining a relative weight of recyclable items withrespect to a weight of a total number of items is disclosed. In thisembodiment, the method includes reading an identifier respectivelyassociated with at least some of the total number of items, anddetermining the number of items detected by sensors and the number ofrecyclable items by detecting the number of identifiers associated withthe recyclable items. The computer also determines a total weight of therecyclable items by multiplying the number of identifiers associatedwith the recyclable items by the weight of each recyclable item. Inaddition, the computer receives a weight from a scale measuring thetotal weight of the total number of items. Finally, the computercomputes the relative weight by dividing the combined weight of allrecyclable items by the weight of the total number of items. Thecomputing of quality, both by number and by weight, can be performed attimes so that the sorting process can be adjusted based on an interimcomputation.

In yet another embodiment of the present invention, acomputer-implemented system for determining a quantity of recyclableitems with respect to a total number of items is disclosed. The systemincludes a reader for reading an identifier respectively associated withat least some of the total number of items. A computer receivesinformation associated with each identifier and determines a number ofidentifiers associated with recyclable items, and a total number ofitems. The computer also determines the relative quantity of recyclableitems by dividing the number of identifiers associated with therecyclable items by the total number of items.

In a further embodiment of the present invention, a computer-implementedsystem is provided for determining a relative weight of recyclable itemswith respect to a total number of items. The system includes a readerfor reading an identifier respectively associated with at least some ofthe items, and a scale for determining a weight of the total number ofitems. A computer computes the relative weight of recyclable items bydetermining a first weight by multiplying the number of identifiersassociated with the recyclable items by the weight of each recyclableitem, and dividing the first weight by the weight of the total number ofitems.

BRIEF DESCRIPTION OF THE DRAWINGS

The Detailed Description including the description of preferred systemsand methods embodying features of the invention will be best understoodwhen read in reference to the accompanying figures, wherein:

FIG. 1 is an exemplary block diagram of a quality control system inaccordance with an embodiment of the present invention.

FIG. 2 is an exemplary flow diagram for determining a relative qualityof sorted recoverable items in accordance with an embodiment of thepresent invention.

FIG. 3 is an exemplary flow diagram for determining a quality of desireditems in accordance with an embodiment of the present invention.

FIG. 4 is an exemplary table of a processed materials data repository inaccordance with an embodiment of the present invention.

FIG. 5 an exemplary radio frequency identifier data repository inaccordance with an embodiment of the present invention.

DESCRIPTION OF EMBODIMENTS OF THE INVENTION

FIG. 1 is an exemplary block diagram of a quality control system 100 inaccordance with an embodiment of the present invention. Quality controlsystem 100 includes central computer 110, recoverables sorting station126 for sorting recoverable items 138, and radio frequencyidentification (RFID) reader 128 for reading a plurality of RFID tags140 attached to recoverable items 138 and contaminate items 142.Contaminate items 142 are those items in recoverables bin 134 which aremis-sorted, and which reduce the quality of the sorted items. As usedherein, recoverable items 138 are items that are made of a particularmaterial of interest, such as aluminum or plastic. Contaminate items 142are items that are items that are not made of a particular material ofinterest. For example, recoverable items 138 of aluminum may be desired.In this case, plastic items and paper items would be contaminate items142, since it is only items of aluminum that are of interest.Recoverable items 138 may also be called recyclable items, since therewould no desire to recover an item if it could not be recycled.

System 100 also includes sensor 132 for sensing the number ofrecoverable items 138 and contaminate items 142, counter 130 forconverting the number of items 138, 142, recoverables bin 134 forstoring recoverable items 138 and contaminate items 142, and scale 136for weighing the recoverable items 138 and contaminate items 142.

Central computer 110 is a standard computer system that includesindustry-standard components, such as a processor 112, user interface114, and communications link 116. Central computer 110 further includesquality control software 120 and one or more databases. This can includeRFID database 122 that contains information corresponding to datacontained within a RFID tag, as will be discussed in connection withFIG. 5. This can also include a processed materials database 124 forstoring a record of all material deposited in recoverables bin 134, aswill be discussed in connection with FIG. 4.

Processor 112 can be a standard microprocessor, such as a Pentium® or aPowerPC® microprocessor device. User interface 114 can be a standardcomputer user interface for inputting and displaying data, such as akeyboard and mouse, a touch screen for inputting data, and a computerdisplay with the accompanying menus and prompt regions. Communicationslink 116 can be a standard wired or wireless communications link thatfacilitates the exchange of data between processor 112 and qualitycontrol software 120 and the data collection devices of the system thatinclude, for example, RFID reader 128, counter 130, sensor 132, andscale 136.

Quality control software 120 analyzes RFID data received from RFID tags140 of recoverable items 138 and contaminate items 142 via RFID reader128, data received from counter 130, and scale data received from scale136. This analysis can be performed in conjunction with RFID database122. RFID database 122 may contain a record of RFID data that isassociated with recoverable 138 and/or and contaminate items 142, whichmay include banned and/or special waste items. For example, RFIDdatabase 122 can contain a record of specific RFID data associated withglass containers, plastic containers, aluminum containers, and/or paperproducts, as well as any banned material and/or special waste items. Thedata can be a unique identifier associated, for example, with each typeor class of material. Quality control software 120 can cross referencethe data stored in RFID database 122 with RFID data received from RFIDreader 128 to determine, for example, the material type of each wasteitem. An exemplary RFID database 122 is described in connection withFIG. 5.

Processed materials database 124 contains a record of materials andquantities thereof deposited in recoverables bin 134. Quality controlsoftware 120 may utilize processed materials database 124 to determine ameasure of sort quality. The information stored within processedmaterials database 124 can include or utilize a cross-reference, forexample, to a collection of materials with information pertaining tocompany brand information, material type, whether the item is a bannedor hazardous item, handling instructions and/or item weight. Databases122 and 124 reside in a memory device, such as a hard disk drive (notshown), and may be implemented using a standard database.

Recoverables sorting station 126 collects materials that are targetedfor recycling. The sorting mechanisms within each recoverables sortingstation 126 can be diverters such as air jets, switching devices,magnets, eddy currents, and/or mechanical arms. Recoverables bin 134 isany type of container, within which a specific type of recoverable iscollected temporarily.

Each RFID tag 140 is a standard wireless device for identifying items,such as recoverable items 138 and contaminate items 142. A RFID tag isformed of a microchip that is attached to an antenna. Data used inconnection with RFID database 122 can be stored on the microchip in astandard manner.

RFID reader 128 can be a commercially available RFID tag reader system,such as the TI RFID system, manufactured by Texas Instruments (Dallas,Tex.). RFID reader 128 scans RFID tags 140, extracts the data containedwithin the tags 140, and transmits the data to central computer 110.

Sensor 132 is a commercially available position or proximity sensordevice that detects the presence of an object, without physical contact.For example, sensor 132 is an inductive, capacitive, or ultrasonicproximity sensor, such as that supplied by Omron Electronics LLC(Schaumburg, Ill.).

Counter 130 can be a standard counter device that can maintain a countin response to an input signal. Counter 130 may be a commerciallyavailable standalone device or, alternatively, a standard binary counterlogic function that is integrated into central computer 110. Thecombination of sensor 132 and counter 130 is used to count the totalnumber of objects (recoverable items 138 and contaminate items 142) thatare deposited into recoverables bin 134. Scale 136 is a generalindustrial weighing scale, such as the Siltec WS2000L, distributed byPrecision Weighing Balances (Bradford, Mass.), that is used to weighrecoverables bin 134 including its contents.

When system 100 is operating, recoverable items 138 and contaminateitems 142 are sorted, recorded, counted, deposited into recoverables bin134, and weighed by scale 136. After the recording and countingprocesses, the collected data can be transmitted to central computer110.

At the beginning of the sorting process, counter 130 is reset to a valueof zero, and at least a portion of processed materials database 124 ismade available for use with the current sorting process. Additionally,scale 136 can be calibrated, either by recording an empty weight ofrecoverables bin 136 or by adjusting scale to read “empty” with theweight of recoverables bin 136. Once the sorting process begins,presorted recoverable items 138 are transferred along a conveyancemechanism (not shown) to recoverables sorting station 126. For example,if recoverables sorting station 126 is a sorting station that isdedicated to sorting aluminum containers, recoverable items 138 thatfeed recoverables sorting station 126 have been presorted to include ahigh percentage of aluminum containers. However, the presort process isnot perfect and, thus, a relatively small percentage of contaminants orother material types (e.g., plastic or glass containers) are present inthis presorted stream. To improve the quality of the sort, a secondsorting operation can be performed at recoverables sorting station 126.

After recoverable items 138 and contaminate items 142 departrecoverables sorting station 126, each respective RFID tag 140 isscanned by RFID reader 128. The data stored on RFID tags 140 istransmitted to central computer 110 via communications link 116.Subsequently, RFID data of each recoverable item 138 and contaminateitems 142 is stored in processed materials database 124, as will bediscussed in connection with FIG. 4.

Next, recoverable items 138 and contaminate items 142 are transporteddownstream and deposited into recoverables bin 134. During this stage,sensor 132 detects each recoverable item 138 and contaminate item 142passing within its field of view. Sensor 132 communicates with counter130 to count each recoverable item 138 and contaminate item 142 passingby.

At the completion of the sorting process, such as when recoverables bin134 is full, the value of counter 130, which represents the total numberof recoverable items 138 and contaminate items 142 in recoverables bin134, is transmitted to central computer 110 via communications link 116and stored, for example, in processed materials database 124.Additionally, the weight of the items (e.g., recoverable items 138 andcontaminate items 142) in recoverables bin 134 is transmitted from scale136 to central computer 110 for storage, for example, in processedmaterials database 124.

Finally, quality control software 120 operates on the data stored inprocessed materials database 124. Quality control software 120calculates the percent quality of the final sorted materials withinrecoverables bin 134 using RFID database 122.

To detect banned waste, data read from the identifiers, which is storedin processed materials database, can be compared to reference datastored within another data repository 124. For example, if an ID of 5922was read as shown in row 406 of processed materials database 124 in FIG.4, this value could be searched for in RFID database 122, an exemplaryembodiment of which is shown in FIG. 5. The cross-referencing of acommon ID 402 (e.g., 5922 in row 406) indicates, in this instance, thatbanned waste has been found, as indicated by column 506 in FIG. 5, andan alert should be sounded.

Quality control software 120 may be used to analyze the identifiers 402stored in processed materials database 124. For example, software 120may cross-reference the identifier 402 data of processed materialsdatabase 124 to that of RFID database 122, as shown in FIG. 5. In thisinstance, a common identifier in column 402 of processed materialsdatabase 124 and RFID database 122 identifies a common item or material(as per the example above).

In addition, the identifier 402 data of processed materials database 124may also be cross-referenced to a Resource Conservation and RecoveryAct/Department of Transportation (RCRA/DOT) database (not shown),available from the U.S. Environmental Protection Agency (EPA). Qualitycontrol software 120 may also query another third party remote bannedmaterial database for banned materials information if there isinsufficient information in the RCRA/DOT database to identify thematerial. In doing so, quality control software 120 may determine thetype items associated with the item identifier 402 in processedmaterials database 124 to determine if any of the items may, forexample, be banned waste.

If any banned waste items are identified, operations personnel of MRFquality control system 100 are notified, and appropriate action is takento handle the banned waste. For example, with regard to FIG. 5, thisinformation may be stored in column 506. For the example ID of 5922 (row406) above, personnel would be warned to use protective gloves.Notification can be made by an audio or visual alert. Audio/visual alertmechanism can be a buzzer, beeper, tone, flashing light emitting diode(LED), that notifies operations personnel that a banned waste item hasbeen detected. Audio/visual alert mechanism can also be implemented on acomputer using its visual display and/or its audio capabilities.

FIG. 2 is a flow diagram for determining a relative quality of sortedrecoverable items 138. At step 210, the sort criterion of recoverablessorting station 126 is established. The sort criterion is the type ofmaterial that the sorting process is supposed to obtain. Additionally, aquality criterion is set, which represents the minimum percentage, byitem count or weight, of recoverable items 138 meeting the sortcriterion, that is to be included in recoverables bin 134. Qualitycriterion may be utilized to account for different purchasers havingdifferent requirements for the maximum allowable amount ofcontamination. Both the sort and quality criterion are possible becauseeach recoverables sorting station 126 can collect a specific materialtype, such as aluminum containers.

At step 212, as an initialization task, when recoverables bin 136 isempty, counter 130 is reset to zero, an initial weight from scale 136 iscaptured, and a portion of processed materials database 124 is madeavailable. At step 214, a final sort operation is performed atrecoverables sorting station 126. More specifically, presortedrecoverable items 138 are transferred along a conveyance mechanism (notshown) to recoverables sorting station 126. For example, if recoverablessorting station 126 is dedicated to sorting aluminum containers, therecoverable items 138 that feed recoverables sorting station 126 have,in one or more embodiments, been presorted to include a relatively highpercentage of aluminum containers. However, the presort process isimperfect and, thus, some (lesser) percentage of contaminants or othermaterial types (e.g., plastic or glass containers), with or without RFIDtags 140, are present in this presorted stream.

At step 216, each respective RFID tag 140 is scanned by RFID reader 128as it leaves recoverable sorting station 126. RFID reader 128 transmitsthe RFID data, as it is collected during scanning, to central computer110 via communications link 116. Alternatively, RFID data can be storedby RFID reader 128 or another appropriate device for sending all RFIDdata at once, after scanning has been completed.

At step 218, RFID data (or a portion thereof) read from tag 140 of eachrecoverable item 138 is received by central computer 110 and stored inprocessed materials database 124. Processed materials database 124contains a record of items 138, 142 whose tags 140 have been read, orcan be used to ascertain all items 138, 142 whose tags 140 have beenread, and the quantities of each respective item 138, 142, that weredeposited in recoverables bin 134. Accordingly, processed materialsdatabase 124 will be updated as items 138, 142 are being scanned by RFIDreader 128, and deposited in recoverables bin 134.

In one embodiment, processed materials database 124 utilizes or accessesRFID database 122. RFID database 122 contains a record of RFID data thatis associated with all recoverable 138 and/or contaminate 142 items,which may include hazardous and/or special waste items. In operation,RFID database 122 is cross-referenced (or queried) by quality controlsoftware 120 when it receives RFID data from RFID reader 128.

More particularly, RFID database 122 may contains a record of thespecific RFID data associated with various glass containers, plasticcontainers, aluminum containers, and/or paper products, as well as anybanned material, such as a hazardous and/or special waste items. Asshown in FIG. 5, one embodiment of RFID database 122 includes, forexample, ID 402, material type 502, banned item status 504, specialhandling instructions 506, company brand 508, and weight 510information. Additional information such as, for example, disposal costper item may also be stored or accessed by RFID database 122.

In operation, and RFID reader 128 scans the tag 140 of each item 138,142, and quality control software 120 accesses RFID database 122 todetermine the item 138, 142 being scanned. For example, if an ID 402 of1001 is scanned (row 418, FIG. 5), quality control software 120 maypopulate processed material database 124 each time that an item 138, 142having an ID of 1001 is scanned. As shown in FIG. 4, row 418 indicatesthat, at a given point in time for a given recoverables bin 134, 9800items having ID of 1001 have been scanned and are in recoverables bin134. Of course, as additional items 138, 142 having the same or otherIDs are scanned by RFID reader 128, processed materials database 124will be updated accordingly.

At step 220, recoverable items 138 that pass through recoverablessorting station 126 are transported downstream and deposited intorecoverables bin 134. At step 222, sensor 132 detects each item passingwithin its field of view. This includes the detection of bothrecoverable 138 and contaminate items 142. Counter 130 is incommunication with sensor 132 and is incremented each time sensor 132detects a new item.

At step 224, when recoverables bin 134 is full, the value of counter 130represents the total combined number of recoverable items 138 andcontaminate items 142 in recoverables bin 134. This value is transmittedto central computer 110, and can be stored, for example, in processedmaterials database 124. Additionally, scale data from scale 136, whichindicates the weight of recoverable items 138 and contaminate items 142in recoverables bin 134 when full, may be transmitted to centralcomputer 110 and stored, for example, in processed materials database124. Furthermore, processed materials database 124 can store additionalRFID data, such as shown in FIG. 5, associated with each fullrecoverables bin 134.

At step 226, quality control software 120 uses processed materialsdatabase 124 to determine a total number of recoverable items 138 withinrecoverables bin 134 that meet the sort criterion, and the total numberof contaminate items 142 that do not. For example, software 120 mayaccess each row (e.g., 418, 420, 410, 412, and 406) of processedmaterials database 124, and utilize the ID 402 of each row to determinethe number of items 404 for each row, and thus the total number of itemsby summing the number of items 404 associated with each row. Qualitycontrol software 120 may also determine which IDs 402 are items ofinterest. For example, it may be determined that only items having an ID402 of 1001 (row 418) are of interest, and are thus the recoverableitems 138. In this case, the total number of contaminate items 142 canbe determined by counting the total number items 404 associated witheach row other than row 418. RFID database 122 can be cross-referencedby using ID 402 field within each database 124, 122 to obtain additionalinformation as may be desired.

At step 228, quality control software 120 performs a calculation todetermine the percentage of recoverables items 138 that meet theexpected sort criterion. This is done by comparing the number ofrecoverable items 138 within recoverables bin 134 to the total number ofall items 138, 142 within recoverables bin 134.

For example, based on the analysis of step 226, quality control software120 determines that RFID data of 9,800 recoverable items 138 is captured(e.g., they are aluminum containers), from row 418 of processedmaterials database 124 (FIG. 4). Based on the counter data that iscaptured in step 224, quality control software 120 determines that atotal of 10,100 items 138, 142 are present within recoverables bin 134,by adding the number of items 404 of rows 418, 420, 410, 406, 412 ofFIG. 4. Accordingly, the percent quality of the sort operation ofrecoverables sorting station 126 is calculated as follows:

# of items that meet the sort criterion÷total number of items in bin

e.g., 9,800÷10,100=0.97 or 97% expected material, and 3% contaminants.

At decision step 230, if the percent quality, as calculated in step 228,is equal to or exceeds the quality criterion set in step 210, then, atstep 232, a record of the percent quality, as calculated in step 228,can be stored, for example, in processed materials database 124. Itshould be understood that if all or substantially all it the items 138,142 in recyclables bin 134 have tags 140 thereon, a percent purity byweight calculation may be performed by quality control software. In thiscase, the number of items associated with rows 418, 420, 410, 406, 412in FIG. 4 are cross referenced by using ID column 402 in FIGS. 4 and 5to determine the weight of each item, as provided by column 510 in FIG.5. Well known and understood mathematical calculations can then beperformed to obtain the total weight of items in rows 418, 420, 410,406, 412 of FIG. 4, and thus the total weight of items in binrecoverables 134.

At step 234, the contents of recoverables bin 134 is transferreddownstream for further processing. For example, the contents ofrecoverables bin 134 can be transferred to a baler, so that items 138,142 can be compacted and baled, for shipment to a customer. One or moreRFID tags can be placed on the bale, indicating the relative quantity ofdesired goods (e.g., aluminum cans) within the bale. The RFID tag datacan also be stored in processed materials database 124.

If at decision step 230 it is determined that the quality is below thequality criterion set in step 210, then, at step 236, the contents ofrecoverables bin 134 can be reprocessed to improve the quality. The goalof reprocessing is to improve the quality of recoverable items 138 byremoving contaminate items 142.

One method for improving quality and removing contaminate items is toreturn the content of recoverables bin 134, in isolation, to the feedstream of recoverables sorting station 126 or some other sort operation(not shown), in order to improve the percent quality of the sort.Another method for removing contaminate items from recoverables bin 134is to manually process the items 138, 142 in recoverables bin 134.Depending on the measured quality and the proximity of the measuredquality to a desired threshold, a sufficient number of contaminate itemscould be removed by hand to meet a minimum quality threshold.Alternatively, the contents of the recoverables bin 134 could be sentback through the sorting process along with other recoverables. This maybe used to average out any pocket of contaminate items 142 in all theitems 138, 142 being processed.

FIG. 3 is a flow diagram for determining the quality of sortedrecoverable items 138 in accordance with another embodiment of thepresent invention. In contrast to the embodiment of FIG. 2, theembodiment of FIG. 3 is based on the weight of recoverable items 138versus the combined weight of items 138, 142. The steps of method 300are the same as or similar to those of method 200 of FIG. 2, except forthe replacement of steps 226 and 228 of method 200 with steps 310 and312, respectively, of method 300. Method steps 310 and 312 are describedas follows.

At step 310, quality control software 120 may utilize RFID database 122to determine the number of recoverable items 138, such as aluminumcontainers, within recoverables bin 134 that meet the expected sortcriterion of step 210, in a manner as described in connection with step218. Furthermore, the data of scale 136, which represents the actualweight of all items 138, 142 in recoverables bin 134 when full, isobtained. The weight may be stored, for example, by computer 110 for anylength of time as may be needed. For example, the weight may be storedin processed materials database 124.

At step 312, quality control software 120 determines the percent qualityof the sort operation by comparing the expected combined weight of allrecoverable items 138 within recoverables bin 134 that meet the expectedsort criterion, to the actual weight of all items 138, 142 inrecoverables bin 134 when full. For example, based on the analysis ofstep 226, using FIG. 4, row 418, quality control software 120 determinesthat RFID data of 9,800 recoverable items 138 having an ID of 1001 wascaptured that meet the sort criterion of step 210 (e.g., they arealuminum containers). Using RFID database 122, quality control software120 can calculate the expected weight of the 9,800 items which met thesort criterion. For example, quality control software 120 accesses row418, and determines that the weight of item 1001 is 0.51 ounces, usingrow 418 and column 510 of FIG. 5. Therefore, quality control software120 calculates the combined weight of 9,800 recoverable items 138 to beapproximately 4,998 ounces (9800 items×0.51 ounces per item). Then,using the weight of the full recoverables bin 134 measured by scale 136,quality control software can determine the percent quality of the sortoperation as follows:

Combined weight of items that meet the sort criterion÷actual weight ofthe contents of the bin (assume the scale measured 5,500 ounces) yields4,998/5,500=0.909, or 90.9% quality of recoverable items 138, andtherefore 10.1% contaminant items 142.

The process for computing the quality of the sorted items both byquantity and by weight can be performed before recoverables bin 134 isfull. For example, a quality of the sorting process could be computedperiodically, continuously, or at other times, during the sortingprocess. The interim determinations of quality may be used like feedbackto improve the quality of the sorting process by adjusting how it isdone. For example, if the sort quality was at 85%, but 90% was desired,items 138, 142 could be sorted more slowly by reducing a conveyor beltspeed. Alternatively, instead of slowing the sorting process down, moreresources could be applied to the sorting process, for example, byadding additional personnel to detect and remove items not meeting thesort criterion.

FIG. 4 is an exemplary database table of processed materials database124 in accordance with an embodiment of the present invention. ID column402 stores an identifier associated with each item 138, 142, that isobtained by scanning RFID tags 140. Column 404 represents the number ofeach item having a particular ID. For example, as shown in row 418,there are 9800 items that have been scanned by reader 128 having an IDof 1001.

FIG. 5 is an exemplary database table of RFID database 122 in accordancewith an embodiment of the present invention. Column 402 stores the IDvalue, and is used to match the information scanned by reader 128 fromRFID tag 140. Exemplary information provided by RFID tag 140 is shown incolumns 502, 504, 506, 508, and 510. Column 502 provides the type ofmaterial that corresponds to the scanned information. Columns 504 and506 respectively indicate if an item is a banned waste item, or whetherthe item requires special handling. In either case, central computer 110can trigger, for example, a visual and/or audible alarm indicating thatsuch circumstance(s) exist. Central computer 110 may also providewritten instructions corresponding to column 506. Such instructions mayeither be visually provided on a monitor associated with centralcomputer 110, or printed by a printer associated with central computer110. Column 508 indicates that company that manufactures the item 138,142 or brand of the item 138, 142. Column 510 indicates the weight ofthe item 138, 142.

Returning now to FIG. 4, it should be understood that FIG. 4 may alsoinclude additional information. For example, if desired, FIG. 4 may alsoinclude for each ID 402 one or more of type of material 502, banned item504 status, special handling instructions 506 and/or company brand 508.In addition, processed materials database 124 may also include, forexample, the computed percent quality as calculated in step 228 (FIG. 2)and/or step 312 (FIG. 3) as discussed herein.

The many features and advantages of the invention are apparent from thedetailed specification, and thus, it is intended by the appended claimsto cover all such features and advantages of the invention which fallwithin the true spirit and scope of the invention. Further, sincenumerous modifications and variations will readily occur to thoseskilled in the art, it is not desired to limit the invention to theexact construction and operation illustrated and described, andaccordingly, all suitable modifications and equivalents may be resortedto, falling within the scope of the invention. While the foregoinginvention has been described in detail by way of illustration andexample of preferred embodiments, numerous modifications, substitutions,and alterations are possible without departing from the scope of theinvention defined in the following claims.

1. A computer-implemented method for determining a relative quantity ofrecyclable items with respect to a total number of items: reading anidentifier respectively associated with at least some of the totalnumber of items; receiving by the computer a number of identifiersassociated with the recyclable items; receiving at the computer a totalnumber of items; and computing the relative quantity of recyclable itemsby dividing the number of identifiers associated with the recyclableitems by the total number of items.
 2. The computer-implemented of claim1, further comprising removing at least a portion of the total number ofitems when the relative quantity is less than a predetermined threshold.3. The computer-implemented method of claim 1, wherein the identifierscomprise radio frequency identifier tags.
 4. The computer-implementedmethod of claim 3, further comprising removing at least a portion of thetotal number of items when the relative quantity is less than apredetermined threshold.
 5. The computer-implemented method of claim 1,further comprising the computer accessing a data repository to determinethe number of identifiers associated with the recyclable items.
 6. Thecomputer-implemented method of claim 5, further comprising generating analert if an identifier is associated with a banned waste item.
 7. Thecomputer-implemented method of claim 1, further comprising generating analert if an identifier is associated with a banned waste item.
 8. Acomputer-implemented method for determining a relative weight ofrecyclable items with respect to a weight of a total number of items,comprising: reading an identifier respectively associated with at leastsome of the total number of items; determining by the computer a numberof identifiers associated with the recyclable items; determining by thecomputer a total weight of the recyclable items by multiplying thenumber of identifiers associated with the recyclable items by the weightof each recyclable item; receiving a weight of the total number ofitems; and computing the relative weight by dividing the total weight ofthe recyclable items by the weight of the total number of items.
 9. Thecomputer-implemented of claim 8, further comprising removing at least aportion of the total number of items when the relative weight is lessthan a predetermined threshold.
 10. The computer-implemented method ofclaim 8, wherein the identifiers comprise radio frequency identifiertags.
 11. The computer-implemented of claim 10, further comprisingremoving at least a portion of the total number of items when therelative weight is less than a predetermined threshold.
 12. Thecomputer-implemented method of claim 8, further comprising the computeraccessing a data repository to determine a weight of the recyclableitems.
 13. The computer-implemented method of claim 12, furthercomprising generating an alert if an identifier is associated with abanned waste item.
 14. The computer-implemented method of claim 8,further comprising generating an alert if an identifier is associatedwith a banned waste item.
 15. The computer-implement method of claim 8,wherein computing the relative weight is done regularly.
 16. Thecomputer-implemented method of claim 8, further comprising sorting thetotal number of items, wherein the sorting is adjusted based on thecomputed relative weight of the recyclable items.
 17. Acomputer-implemented system for determining a quantity of recyclableitems with respect to a total number of items, comprising: a reader forreading an identifier respectively associated with at least some of thetotal number of items; a computer that determines: a number ofidentifiers associated with the recyclable items; the total number ofitems; and the relative quantity of recyclable items by dividing thenumber of identifiers associated with the recyclable items by the totalnumber of items.
 18. The computer-implemented system of claim 17,wherein the identifiers comprise radio frequency identifier tags. 19.The computer-implemented system of claim 17, further comprising thecomputer accessing a data repository to determine the number ofidentifiers associated with the recyclable items and the number ofidentifiers associated with the total number of items.
 20. Acomputer-implemented system for determining a relative weight ofrecyclable items with respect to a total number of items, comprising: areader for reading an identifier respectively associated with at leastsome of the total number of items; a scale for determining a weight ofthe total number of items; and a computer that computes the relativeweight of recyclable items by: determining a first weight by multiplyingthe number of identifiers associated with the recyclable items by theweight of each recyclable item; and dividing the first weight by theweight of the total number of items.
 21. The computer-implemented systemof claim 20, wherein the identifiers comprise radio frequencyidentification tags.
 22. The computer-implemented system of claim 21,further comprising a data repository storing an identifier associatedwith the recyclable items.